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configuration: |
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batch_size: 64 |
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optimizer: torch.optim.AdamW |
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lr: 0.001 |
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trainer: experiment_setup.train_loop |
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scorer: experiment_setup.score |
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model: models.clipseg.CLIPDensePredT |
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lr_scheduler: cosine |
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T_max: 20000 |
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eta_min: 0.0001 |
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max_iterations: 20000 |
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val_interval: null |
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dataset: datasets.phrasecut.PhraseCut |
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split_mode: pascal_test |
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mode: train |
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mask: text_and_crop_blur_highlight352 |
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image_size: 352 |
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normalize: True |
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pre_crop_image_size: [sample, 1, 1.5] |
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aug: 1new |
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with_visual: True |
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split: train |
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mix: True |
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prompt: shuffle+ |
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norm_cond: True |
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mix_text_min: 0.0 |
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out: 1 |
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version: 'ViT-B/16' |
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extract_layers: [3, 7, 9] |
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reduce_dim: 64 |
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depth: 3 |
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loss: torch.nn.functional.binary_cross_entropy_with_logits |
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amp: True |
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test_configuration_common: |
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normalize: True |
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image_size: 352 |
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metric: metrics.FixedIntervalMetrics |
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batch_size: 1 |
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test_dataset: pascal |
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sigmoid: True |
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test_configuration: |
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- |
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name: pas_t |
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mask: text |
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- |
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name: pas_h |
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mask: blur3_highlight01 |
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- |
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name: pas_h2 |
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mask: crop_blur_highlight352 |
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columns: [name, |
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pas_t_fgiou_best, pas_t_miou_best, pas_t_fgiou_ct, |
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pas_h_fgiou_best, pas_h_miou_best, pas_h_fgiou_ct, |
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pas_h2_fgiou_best, pas_h2_miou_best, pas_h2_fgiou_ct, pas_h2_fgiou_best_t, |
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train_loss, duration, date |
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] |
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individual_configurations: |
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- {name: rd64-uni-phrasepas5i-0, remove_classes: [pas5i, 0], negative_prob: 0.2, mix_text_max: 0.5, test_configuration: {splits: [0], custom_threshold: 0.24}} |
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- {name: rd64-uni-phrasepas5i-1, remove_classes: [pas5i, 1], negative_prob: 0.2, mix_text_max: 0.5, test_configuration: {splits: [1], custom_threshold: 0.24}} |
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- {name: rd64-uni-phrasepas5i-2, remove_classes: [pas5i, 2], negative_prob: 0.2, mix_text_max: 0.5, test_configuration: {splits: [2], custom_threshold: 0.24}} |
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- {name: rd64-uni-phrasepas5i-3, remove_classes: [pas5i, 3], negative_prob: 0.2, mix_text_max: 0.5, test_configuration: {splits: [3], custom_threshold: 0.24}} |
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- {name: rd64-phrasepas5i-0, remove_classes: [pas5i, 0], negative_prob: 0.0, test_configuration: {splits: [0], custom_threshold: 0.28}} |
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- {name: rd64-phrasepas5i-1, remove_classes: [pas5i, 1], negative_prob: 0.0, test_configuration: {splits: [1], custom_threshold: 0.28}} |
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- {name: rd64-phrasepas5i-2, remove_classes: [pas5i, 2], negative_prob: 0.0, test_configuration: {splits: [2], custom_threshold: 0.28}} |
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- {name: rd64-phrasepas5i-3, remove_classes: [pas5i, 3], negative_prob: 0.0, test_configuration: {splits: [3], custom_threshold: 0.28}} |
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- {name: bl64-phrasepas5i-0, model: models.clipseg.CLIPDenseBaseline, remove_classes: [pas5i, 0], reduce2_dim: 64, negative_prob: 0.0, test_configuration: {splits: [0], custom_threshold: 0.24}} |
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- {name: bl64-phrasepas5i-1, model: models.clipseg.CLIPDenseBaseline, remove_classes: [pas5i, 1], reduce2_dim: 64, negative_prob: 0.0, test_configuration: {splits: [1], custom_threshold: 0.24}} |
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- {name: bl64-phrasepas5i-2, model: models.clipseg.CLIPDenseBaseline, remove_classes: [pas5i, 2], reduce2_dim: 64, negative_prob: 0.0, test_configuration: {splits: [2], custom_threshold: 0.24}} |
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- {name: bl64-phrasepas5i-3, model: models.clipseg.CLIPDenseBaseline, remove_classes: [pas5i, 3], reduce2_dim: 64, negative_prob: 0.0, test_configuration: {splits: [3], custom_threshold: 0.24}} |
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- {name: vit64-uni-phrasepas5i-0, remove_classes: [pas5i, 0], model: models.vitseg.VITDensePredT, negative_prob: 0.2, mix_text_max: 0.5, lr: 0.0001, test_configuration: {splits: [0], custom_threshold: 0.02}} |
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- {name: vit64-uni-phrasepas5i-1, remove_classes: [pas5i, 1], model: models.vitseg.VITDensePredT, negative_prob: 0.2, mix_text_max: 0.5, lr: 0.0001, test_configuration: {splits: [1], custom_threshold: 0.02}} |
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- {name: vit64-uni-phrasepas5i-2, remove_classes: [pas5i, 2], model: models.vitseg.VITDensePredT, negative_prob: 0.2, mix_text_max: 0.5, lr: 0.0001, test_configuration: {splits: [2], custom_threshold: 0.02}} |
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- {name: vit64-uni-phrasepas5i-3, remove_classes: [pas5i, 3], model: models.vitseg.VITDensePredT, negative_prob: 0.2, mix_text_max: 0.5, lr: 0.0001, test_configuration: {splits: [3], custom_threshold: 0.02}} |
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